IOSR Journal of Computer Engineering (IOSR-JCE)

1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 1, Ver. II (Jan. 2014), PP 75-79
www.iosrjournals.org
www.iosrjournals.org 75 | Page
An Improvement on Route Recovery by Using Triangular Fuzzy
Numbers on Route Errors in MANET
Sara Aliabadi¹, Mehdi Agha Sarram¹
¹Department of Computer Science, Islamic Azad University Science and Research Branch Yazd, Yazd, Iran
Abstract: Based on mobile nature in MANET, there is no doubt that all routing protocols have some route
errors. Usually, routing protocols try to recover a route after a route error has been happened on an exact route
to destination. This kind of route recovery could make more packet loss and also more time waste. This project
adds Triangular Fuzzy Numbers to prediction of route errors and make route recovery as parallel of packet
sending. Indeed, any node in this project uses a route error counter and an error prediction based on Fuzzy
algorithm to recover its routes before an exact route error on its route discovery has been happened. There is
no doubt that using suggested prediction cannot solve all route errors; but it could help routing protocols to
improve their route recovery algorithm.This project uses DSR as one of the standard MANET routing protocols
to simulate the results.
Keywords: MANET, Fuzzy, Triangular Numbers, DSR, Routing
I. Introduction
A wireless mobile ad hoc network (MANET) is a particular type of wireless network in which an
association of mobile nodes forms a multi-hop radio temporary network in a decentralize manner without any
support of a fixed infrastructure. Each mobile node acts as both a terminal and a router, and the control of the
network activity is distributed to these nodes. Mobile nodes communicate over wireless links which typically
have less bandwidth than wired networks. In addition, mobile nodes have lower battery power and lower
computation ability. The network topology is generally dynamic because the connectivity among the nodes may
change with time due to nodal mobility, the effect ofradio communication, and power limitations. Thesefeatures
of MANET have posed a lot of challenges indesigning an effective, reliable and scalable routingprotocol.
Lost routes recovery is one of the major challenges in MANET routing protocols which could make a route
more or less effective on packet loss during packet sending. Usually, routing protocols in MANET provide route
error to inform other nodes that a node is gone and route through that node are not usable any more. In this case,
node will recover their routes after a route error has been happened. Thus, packets which are sent during route
recovery will lose.
A fuzzy number is a quantity whose value is imprecise, rather than exact as is the case with "ordinary"
(single-valued) numbers. Any fuzzy number can be thought of as a function whose domain is a specified set
(usually the set of real numbers, and whose range is the span of non-negative real numbers. Triangular Fuzzy
Numbers use three sets of value to estimate the average situation of any system.
First part of this article is to explain DSR and how it works. Then, the second part is going to determine Fuzzy
Triangular Numbers and project suggestion to predict route error. Finally, we simulate our findings by NS2 to
prove our recovery improvement on MANET routing.
II. DSR
A Mobile Ad Hoc Network, also called a MANET, is an autonomous collection of mobile nodes
forming a dynamic wireless network. The administration of such a network is decentralized. In this kind of
network each node acts both as host and router and forwards packets for nodes that are not within transmission
range of each other. A MANET provides a practical way to rapidly build a decentralized communication
network in areas where there is no existing infrastructure or where temporary connectivity is needed.
The changing topology of MANETs and use of the wireless medium justify the need fordifferent routing
protocols than those developed for wired networks or multi-cell environments.Various routing protocols have
been proposed in the IETF MANET working group to addressthe problem of decentralized routing.
The Dynamic Source Routing (DSR) protocol was designed especially for MANET applications. Its
main feature is that every data packet follows the source route stored in its header. This route gives the address
of each node through which the packet should be forwarded in order to reach its final destination. Each node on
the path has a routing role and must transmit the packet to the next hop identified in the source route.

2. An Improvement on Route Recovery by Using Triangular Fuzzy Numbers on Route Errors in MANET
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Each node maintains a Route Cache in which it stores every source route it has learned. When a node needs to
send a data packet, it checks first its route cache for a source route to the destination. If no route is found, it
attempts to find one using the route discovery mechanism.
A monitoring mechanism, called route maintenance, is used in each operation along a route. This
mechanism checks the validity of each route used.
The route maintenance mechanism ensures that the paths stored in the route cache are valid. If the data link
layer of a node detects a transmission error, the node creates a Route Error packet and transmits it to the original
sender of the data packet. This Route Error packet indicates which link is “broken”. When a node receives a
Route Error packet, it removes the link in error from its route cache and for each route containing this link,
truncates the route from the hop before the broken link.
III. Fuzzy Triangular Numbers and Recovery Algorithm
Route updating can help routing protocols to reduce packet loss and improve QoS. Indeed, MANETs
have a mobile nature; so topology changes in them frequently. This mobile nature effects on the routes and
make them unusable after a while. So, all MANET routing protocols need a route updating algorithm.
In this project, we use Triangular Fuzzy Numbers to make the route updating time dependent. In this case, we
forecast a time for route updating and make this time error dependent based on Triangular Numbers. If the route
error came from a direct node in a route, other nodes will update that route immediately. Otherwise, nodes
which received route error will increase their route error counter and operate triangular equation. The result of
Triangular equation should multiply to forecast time and subtract from it.
In order to consider the fuzzy route recovery using the triangular fuzzy numbers which were based on statistical
data, we need the following definitions.
Definition 1: A fuzzy set is called a level α fuzzy interval, where 0 ≤ α ≤ 1 and we denote it by [p,q;α], if its
membership function is:
[ ]( ) { (1)
Definition 2: ã is called a fuzzy point, if its membership function on R = (− ∞, ∞) is
( ) { (2)
The family of all fuzzy sets on R which we denote as satisfies the following two conditions. Let D∈Fs.
ThenDsatisfies ( ) and ( ) below.
( ) The left and right hand side of the α-level set of D, ( ) and ( ) exist. We denoteit as D(α) =
[ ( ) ( )].
( ) ( ) and ( ) are integrable for α ∈ [0, 1].
By using Triangular definition, we can reach the following equation to guess when a route protocol should
update or recover its route table.
( )
{
∈ ( ]
∈ ( ]
(3)
By using equation 3, we can divide mobile network errors to five parts. First, if the error comes from exact node
on the route, other nodes will recover their routes immediately. Otherwise, they count the route errors and put
the counter in equation 3. In this case, if the route errors were less than a, the network is safe and they do
recovery as usual. While, if the route errors go over than a and less than m, they will multiply the result of
equation 3 to their usual recovery time and subtract the result from left recovery time. It will be same for route
errors which are more than m and less than b. For route errors which are more or equal by b, the network is not
safe and nodes will recover their route immediately. Note that, in this case, the route error counter will be
change to zero after any route recovery.
IV. Simulation Results
We addour findings on DSR and simulated it by NS2 for 5, 10, 15, 20, 25, 30, 35, and 40 nodes. Whereas
every simulation results may have some exceptions, we simulated the F-DSR in some times and made our
decision based on their average.
1.1 End to End Delay
End to End Delay is the most important result to prove the success of each routing protocol. The results
of simulation show that the F-DSR works more proper than standard DSR. We can see that the End to End
Delay in F-DSR is less than Standard DSR. Also, F-DSR has more success during node population increment.

3. An Improvement on Route Recovery by Using Triangular Fuzzy Numbers on Route Errors in MANET
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1.2 Packet Delivery Rate
Packet Delivery Rate is our final comparison between F-DSR and Standard DSR. There is no doubt that the
results of simulation show that the packet delivery rate increased in F-DSR compare on Standard ones.
V. Conclusion
Based on MANET mobility nature, there is always some route errors during packet sending. Usually,
MANET routing protocols recover their routes after a route error has been happened. This kind of route
recovery may cause to increase packet loss during packet sending. In this project we added Fuzzy Triangular
Numbers into routing protocols in MANET to predict route errors and do route update in parallel of packet
sending. For simulating our findings, we added our error prediction in DSR and simulated it by NS2. The results
show that our route recovery algorithm can help DSR to reduce packet loss percentage and end to end delay by
parallel route recovery.
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